# DeepSeek-V4 Flash RL on AMD Instinct MI308X GPUs with an AITER-Backed RL Stack

> Source: <https://rocm.blogs.amd.com/ecosystems-and-partners/deepseek-v4-mi308-aiter-backed-rl/README.html>
> Published: 2026-10-28 00:00:00+00:00

We demonstrate end-to-end DeepSeek-V4 Flash reinforcement learning with an
AITER-backed AMD RL stack on 24 AMD Instinct
MI308X GPUs. Our test covers the complete workflow on three MI308X OAM
nodes—not only inference or an
isolated training step, but long-context FP8 rollout, BF16 MoE actor training,
online RDMA weight updates, evaluation, and checkpoint recovery. Training and
inference run as disaggregated services: two MI308X nodes host a BF16 actor
that preserves the numerical stability required by gradient computation and
optimizer updates, while a dedicated third MI308X node hosts an FP8 rollout
engine whose smaller per-parameter footprint leaves more GPU memory available
for KV cache and longer generated sequences.
Ray places and coordinates both GPU groups. This
experiment demonstrates one tested three-node configuration
for running both rollout inference and RL training on MI308X GPUs.